Research on Intelligent Control System Model of Computer-aided Battlefield Situation Awareness of Armored Vehicles

This project establishes a set of war situation awareness and intelligent control methods for vehicle-mounted combat equipment. Sensor data fusion, Kalman filtering, machine learning and intelligent control are integrated to improve the vehicle’s cognitive level of complex scenes. First, the vehicle-mounted combat environment cognition method based on Kalman filter is studied to achieve online optimization and prediction of multi-source information, thereby reducing the impact of environmental information and improving the accuracy of situational cognition. Secondly, by analyzing external information, the vehicle-mounted combat vehicle can automatically judge and command in combat status. This paper verifies the proposed model through a simulation platform. It shows that this method can achieve accurate perception and intelligent control of vehicle status under complex terrain conditions. The improved environmental cognition accuracy of the personnel carrier is improved by $15 \%$, and the response time of the control system is reduced by $20 \%$. Experiments have shown that this method can improve the accuracy of vehicle situation detection and the responsiveness of vehicle control systems.